Data Scientist

Applicants must meet all qualifications and eligibility requirements by the closing date of the announcement including time-in-grade restrictions, specialized experience and/or education, as defined below. TIME-IN-GRADE: Current federal employees applying for a promotion opportunity must meet time-in-grade (TIG) requirement of 52 weeks of service at the next lower grade level in the normal line of progression for the position being filled.

Basic Requirements Degree: Mathematics, statistics, computer science, data science or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position. OR Combination of education and experience: Courses equivalent to a major field of study (30 semester hours) as shown above in paragraph A above, plus additional education or appropriate experience.

FOR THE GS-13 LEVEL: Applicants must have one year of specialized experience (equivalent to the GS-12 level) that may have been obtained in the private or public (local, county, state, Federal) sectors which demonstrates: Plans, develops, and carries out complex data analysis projects and studies. Develops standards for analyzing, testing, and assessing emerging data analytics technologies and methods. Originates new and improved data analytics applications and strategies.

Provides guidance and recommendations regarding enterprise data analytics challenges and issues. Note: There is no education substitution for this grade level. TRANSCRIPTS are required if: This position requires specific coursework or a degree in a specific field to be basically qualified. This education must have been successfully completed and obtained from an accredited school, college, or university.

Experience refers to paid and unpaid experience, including volunteer work done through National Service programs (e.g., Peace Corps, AmeriCorps) and other organizations (e.g., professional; philanthropic; religious; spiritual; community, student, social). Volunteer work helps build critical competencies and can provide valuable training and experience that translates directly to paid employment. You will receive credit for all qualifying experience, including volunteer experience.

The duties may include, but are not limited to:,Program languages used include Python, SQL, R, and others for data cleaning, integration, and analytics.,Process large unstructured data to support queries and address enterprise business needs. Offers professional guidance on debugging techniques and best practices.,Conduct statistical analyses and applies data science methods to support the transition to data-driven initiatives.,Evaluate and execute data needs throughout the entire data life cycle, including data collection, ingestion, storage, modeling, access, integration, analysis, and decision support.,Create interactive data visualization tools like Tableau, ESRI, R, Python, and Power BI to present analytical results with graphs, charts, dashboards, and other visualizations.,Design data flows and using data systems to create new and modify existing tools for better customer experience.